Phases Of Cyclic Alternating Pattern Research Articles

An expert system for automated classification of phases in cyclic alternating patterns of sleep using optimal wavelet‐based entropy features

AbstractHumans spend a significant portion of their time in the state of sleep, and therefore one's’sleep health’ is an important indicator of the overall health of an individual. Non‐invasive methods such as electroencephalography (EEG) are used to evaluate the ’sleep health’ as well as associated disorders such as nocturnal front lobe epilepsy, insomnia, and narcolepsy. A long‐duration and repetitive activity, known as a cyclic alternating pattern (CAP), is observed in the EEG waveforms which reflect the cortical electrical activity during non‐rapid eye movement (NREM) sleep. The CAP sequences involve various, continuing periods of phasic activation (phase‐A) and deactivation (phase‐B). The manual analysis of these signals performed by clinicians are prone to errors, and may lead to the wrong diagnosis. Hence, automated systems that can classify the two phases (viz. Phase A and Phase B accurately can eliminate any human involvement in the diagnosis. The pivotal aim of this study is to evaluate the usefulness of stopband energy minimized biorthogonal wavelet filter bank (BOWFB) based entropy features in the identification of CAP phases. We have employed entropy features obtained from six wavelet subbands of EEG signals to develop a machine learning (ML) based model using various supervised ML algorithms. The proposed model by us yielded an average classification accuracy of 74.40% with 10% hold‐out validation with the balanced dataset, and maximum accuracy of 87.83% with the unbalanced dataset using ensemble bagged tree classifier. The developed expert system can assist the medical practitioners to assess the person's cerebral activity and quality of sleep accurately.

391 Upper Airway Resistance Syndrome is associated with high Cyclic Alternating Pattern

Abstract Introduction Upper Airway Resistance Syndrome (UARS) is suspected in individuals with excessive daytime sleepiness, fatigue, and sleep fragmentation associated with increased respiratory effort. UARS can negatively impact daytime function. Conventional polysomnography parameters do not demonstrate significant abnormalities in UARS patients but increase in RERAs and arousal index. Cyclic alternating pattern (CAP) is a periodic electroencephalogram activity of non-REM sleep that expresses a condition of sleep instability. The objective of the study was to compare CAP components between UARS patients and health individuals. Methods Fifteen subjects with UARS and 15 age- and sex- matched controls had their sleep study blinded analyzed. UARS criteria were the presence of sleepiness (Epworth Sleepiness Scale – ESS - ≥ 10) and/or fatigue (Modified Fatigue Impact Scale ≥ 38) associated with an apnea/hypopnea index (AHI) ≤ 5 and a respiratory disturbance index (RDI) > 5 events/hour of sleep, and/or flow limitation in more than 30% of total sleep time. Control group criteria were AHI < 5 events/hour, RDI ≤ 5 events/hour and < 30% of TST with flow limitation and ESS < 10, without sleep, clinical, neurological, or psychiatric disorder. CAP electroencephalogram of both groups was analyzed. Results We found higher CAP rate (p = 0.05) and CAP index in N1 stage (p < 0.001) and in N3 stage (p < 0.001) in UARS patients compared to control group. Considering only CAP phase A1 analysis, UARS patients presented higher CAP rate (p = 0.05) and CAP index in N1 stage (p < 0.001) as well as CAP index in N3 stage (p < 0.001) compared to control group. Considering only CAP phase A2 analysis, UARS patients also presented higher number of CAP in N1 stage (p = 0.05). There was no significant difference for CAP phase A3 between groups. Conclusion Although UARS is associated with high arousal index, we found increase in CAP phase A1 and A2, which do not include necessarily AASM arousals, suggesting not only sleep fragmentation but also sleep instability. Support (if any) Associação Fundo de Incentivo à Pesquisa (AFIP) and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP).

Electrophysiological and microstructural features of sleep in children at high risk for depression: a preliminary study

ObjectiveThis preliminary study investigated electrophysiological and microstructural features of sleep in children and adolescents 4–18 years of age who were born to depressed mothers. MethodsA total of 31 healthy subjects (15 male and 16 female) participated in the study. In this sample, 20 children born to mothers diagnosed with Major Depressive Disorder (MDD) were designated as “high-risk”; 11 children born to mothers without a personal history of depression were designated as “low-risk.” Polysomnography including three-channel electroencephalography (EEG) was recorded for one night at the Pediatric Sleep Unit of the University Hospital of Lyon, France. Clinical and demographic data were collected. Sleep architectural parameters were analyzed. Sleep microstructure was assessed with the scoring of cyclic alternating pattern (CAP) and CAP measures were calculated. Spectral analysis was performed, and mean EEG band power was computed for each sleep stage. Sleep electrophysiological features (slow waves and sleep spindles) were detected, and related parameters were analyzed. Data were compared between high- and low-risk groups using Student t tests. ResultsA reduction in low-frequency spindle activity and slow spindles spatio-temporal characteristics over frontal and central derivations, and an altered distribution of CAP phase A subtypes (reduction of A1 over A2–3 ratio) were observed in the high-risk group relative to the low-risk group. ConclusionLimited spindles generation and increased non-rapid eye movement sleep instability, observed in children born to depressed mothers, might reflect functional anomalies in cortical plasticity that could represent a pathogenic factor or an epiphenomenon for MDD.

Can sleep microstructure improve diagnosis of OSAS? Integrative information from CAP parameters.

The scoring of American Academy of Sleep Medicine (AASM) arousal is mandatory for the definition of respiratory event-related arousal (RERA). However there are other EEG activation phenomena, such as A phases of cyclic alternating pattern (CAP) which are associated with respiratory events in non rapid eye movements (NREM) sleep. This study aims at quantifying the additional value of CAP for the definition of respiratory events and sleep alterations in OSAS. Analysis of polysomnographic recordings from nineteen OSAS patients was carried out. Scoring was focused on investigation of the cerebral response to flow limitation (FL) events. For this purpose we used both CAP rules and AASM arousal criteria. While no difference was demonstrated in the arousal index between mild and moderate-severe OSAS patients, CAP time showed a progressive enhancement from normal subjects (152.5±20.76) to mild (180.64±34.76) and moderate-severe (282.27±58.02) OSAS patients. In NREM sleep, only 41.1% of FL events met the criteria for the definition of RERA, while, 75.5% of FL events ended with a CAP A phase and most FL CAP (69.1%) terminated with a CAP phase A3 subtype. Our data indicate that the RERA scoring has a limited accuracy in the detection of FL events. In NREM sleep, CAP rules provided more information than AASM arousal for the definition of respiratory events and sleep alterations in OSAS.

Association between heart rate variability, blood pressure and autonomic activity in cyclic alternating pattern during sleep.

Cyclic alternating pattern (CAP) is frequently followed by changes in heart rate (HR) and blood pressure (BP), but the sequential associations between CAP and autonomic nerve activity have not been studied. The study aimed to reveal the precise changes in heart rate variability (HRV) during phase A of the CAP cycle. Polysomnography was recorded according to the CAP Atlas (Terzano, 2002), and BP and electrocardiogram were simultaneously recorded. The complex demodulation method was used for analysis of HRV and evaluation of autonomic nerve activity. Academic sleep laboratory. Ten healthy males. The increase in HR (median [first quartile - third quartile]) for each subtype was as follows: A1, 0.64 (-0.30 to 1.69), A2, 1.44 (0.02 to 3.79), and A3, 6.24 (2.53 to 10.76) bpm (A1 vs. A2 P < 0.001, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). The increase in BP for each subtype was as follows: A1, 1.23 (-2.04 to 5.75), A2, 1.76 (-1.46 to 9.32), and A3, 12.51 (4.75 to 19.94) mm Hg (A1 vs. A2 P = 0.249, A1 vs. A3 P < 0.001, A2 vs. A3 P < 0.001). In all of phase A, the peak values for HR and BP appeared at 4.2 (3.5 to 5.4) and 8.4 (7.0 to 10.3) seconds, respectively, after the onset of phase A. The area under the curve for low-frequency and high-frequency amplitude significantly increased after the onset of CAP phase A (P < 0.001) and was higher in the order of subtype A3, A2, and A1 (P < 0.001). All phase A subtypes were accompanied with increased heart rate variability, and the largest heart rate variability was seen in subtype A3, while a tendency for less heart rate variability was seen in subtype A1.

EEG segmentation for improving automatic CAP detection

ObjectiveThe aim of this study is to provide an improved method for the automatic classification of the Cyclic Alternating Pattern (CAP) sleep by applying a segmentation technique to the computation of descriptors from the EEG. MethodsA dataset of 16 polysomnographic recordings from healthy subjects was employed, and the EEG traces underwent first an automatic isolation of NREM sleep portions by means of an Artificial Neural Network and then a segmentation process based on the Spectral Error Measure. The information content of the descriptors was evaluated by means of ROC curves and compared with that of descriptors obtained without the use of segmentation. Finally, the descriptors were used to train a discriminant function for the automatic classification of CAP phases A. ResultsA significant improvement with respect to previous scoring methods in terms of both information content carried by the descriptors and accuracy of the classification was obtained. ConclusionsEEG segmentation proves to be a useful step in the computation of descriptors for CAP scoring. SignificanceThis study provides a complete method for CAP analysis, which is entirely automatic and allows the recognition of A phases with a high accuracy thanks to EEG segmentation.

Periodic Leg Movement, Nasal CPAP, and Expiratory Muscles

Periodic leg movements (PLMs) may appear during nasal CPAP titration, persisting despite the elimination of hypopneas. Systematic recordings of expiratory abdominal muscles on the right and left sides with surface electromyographic (EMG) electrodes lateral to navel, and close from the lateral side of abdomen, were added during nasal CPAP titration for treatment of obstructive sleep apnea (OSA). Positive airway pressure was titrated during nocturnal polysomnography, based on analysis of the flow curve derived from the CPAP equipment and EEG analysis, including persistence of phases A2 and A3 of the cyclic alternating pattern (CAP). The requirement was to eliminate American Association of Sleep Medicine (AASM)-defined hypopnea and also flow limitation and abnormal EEG patterns. When CPAP reached valid results, it was lowered at the time of awakening by 2 or 3 cm H(2)O, and titration was performed again. Data collected during a 7-month period on adults with a prior diagnosis of OSA who had received treatment with nasal CPAP regardless of age and sex were rendered anonymous and were retrospectively rescored by a blinded investigator. Eighty-one successively seen patients with PLMs during CPAP titration were investigated. Elimination of AASM-defined hypopnea was not sufficient to eliminate the PLMs observed during the titration; higher CPAP eliminated flow limitation and CAP phases A2 and A3 and persisting PLMs. PLMs were associated with simultaneous EMG bursts in expiratory abdominal muscles. The presence of PLMs during CPAP titration indicates the persistence of sleep-disordered breathing. PLMs during CPAP titration are related to the presence of abdominal expiratory muscle activity.

Distinctive polysomnographic traits in nocturnal frontal lobe epilepsy

To describe the polysomnographic features and distribution of epileptic motor events, in relation to conventional sleep measures and cyclic alternating pattern (CAP) parameters, in 40 untreated patients with nocturnal frontal lobe epilepsy (NFLE). We analyzed the basal polysomnographic recordings of 40 patients (20 male and 20 female; mean age: 31 ± 10 years) with a diagnosis of nocturnal frontal lobe epilepsy. Conventional sleep measures and CAP parameters were assessed. Polysomnographic recordings were subdivided in sleep cycles. The distribution of the epileptic motor events (including minor motor events, paroxysmal arousals, tonic-dystonic, or hyperkinetic seizures and epileptic nocturnal wandering) was analyzed throughout: total sleep time, non-rapid eye movement (NREM) and REM sleep, light sleep (S1 + S2), slow wave sleep (SWS), each sleep cycle, CAP or non-CAP sleep, phase A and phase B of CAP. Only clear epileptic motor events supported by video-polysomnographic evidence were taken into consideration. Polysomnographic findings of patients with NFLE were compared with those of 24 age- and gender-balanced healthy subjects without sleep complaints. Compared to controls, patients with NFLE showed a significant increase in wake after sleep onset, SWS duration, and REM latency, whereas REM sleep duration was significantly lower in NFLE patients. The patients with NFLE showed a significant increase of CAP time, CAP rate (72% vs. 32% in control group), CAP cycles, and mean duration of a CAP sequence. These findings were associated with a significant enhancement of all subtypes of the A phases of CAP (mainly subtype A1). A total of 139 epileptic motor events supported by video-polysomnographic evidence were counted: 98% of all seizures occurred in NREM sleep and 72% of NREM seizures emerged from SWS, the latter being particularly collected in the first sleep cycles and decreasing in frequency together with the progressive decline of deep sleep. Ninety percent of total NREM seizures occurred during a CAP sequence, and CAP-related seizures occurred in association with a phase A. Significant polysomnographic alterations seem to emerge in patients with NFLE (increased REM latency, epileptic fragmentation of SWS, and increase of CAP rate). The analysis of seizure distribution showed that most epileptic events occurred in SWS, with predominance in the first sleep cycle and decreasing in frequency together with the homeostatic decline of SWS across the night. Within the NREM sleep, CAP is a manifestation of unstable sleep and represents a powerful predisposing condition for the occurrence of nocturnal motor seizures, which arise in concomitance with a phase A.

Sleep bruxism and sleep arousal: an experimental challenge to assess the role of cyclic alternating pattern

Rhythmic masticatory muscle activity (RMMA) is the characteristic electromyographic pattern of sleep bruxism (SB), a sleep-related motor disorder associated with sleep arousal. Sleep arousals are generally organised in a clustered mode known as the cyclic alternating pattern (CAP). CAP is the expression of sleep instability between sleep maintaining processes (phase A1) and stronger arousal processes (phases A2 and A3). This study aimed to investigate the role of sleep instability on RMMA/SB occurrence by analysing CAP and electroencephalographic (EEG) activities. The analysis was performed on the sleep recordings of 8 SB subjects and 8 controls who received sensory stimulations during sleep. Baseline and experimental nights were compared for sleep variables, CAP, and EEG spectral analyses using repeated measure ANOVAs. Overall, no differences in sleep variables and EEG spectra were found between SB subjects and controls. However, SB subjects had higher sleep instability (more phase A3) than controls (P= 0·05). The frequency of phase A3 was higher in the pre-REM sleep periods (P < 0·001), where peaks in RMMA/SB activity were also observed (P = 0·05). When sleep instability was experimentally increased by sensory stimuli, both groups showed an enhancement in EEG theta and alpha power (P = 0·04 and 0·02, respectively) and significant increases in sleep arousal and all CAP variables. No change in RMMA/SB index was found within either groups (RMMA/SB occurred in all SB subjects and only one control during the experimental night). These findings suggest that CAP phase A3 may act as a permissive window rather than a generator of RMMA/SB activity in predisposed individuals.

Clonidine Has a Paradoxical Effect on Cyclic Arousal and Sleep Bruxism during NREM Sleep

Clonidine disrupts the NREM/REM sleep cycle and reduces the incidence of rhythmic masticatory muscle activity (RMMA) characteristic of sleep bruxism (SB). RMMA/SB is associated with brief and transient sleep arousals. This study investigates the effect of clonidine on the cyclic alternating pattern (CAP) in order to explore the role of cyclic arousal fluctuation in RMMA/SB. Polysomnographic recordings from a pharmacological study. University sleep research laboratory. Sixteen SB subjects received a single dose of clonidine or placebo at bedtime in a crossover design. Sleep variables and RMMA/SB index were evaluated. CAP was scored to assess arousal instability between sleep-maintaining processes (phase A1) and stronger arousal processes (phases A2 and A3). Paired t-tests, ANOVAs, and cross-correlations were performed. Under clonidine, CAP time, and particularly the number of A3 phases, increased (P≤0.01). RMMA/SB onset was time correlated with phases A2 and A3 for both placebo and clonidine nights (P≤0.004). However, under clonidine, this positive correlation began up to 40 min before the RMMA/SB episode. CAP phase A3 frequency increased under clonidine, but paradoxically, RMMA/SB decreased. RMMA/SB was associated with and facilitated in CAP phase A2 and A3 rhythms. However, SB generation could be influenced by other factors besides sleep arousal pressure. NREM/REM ultradian cyclic arousal fluctuations may be required for RMMA/SB onset.

Small-world network organization of functional connectivity of EEG slow-wave activity during sleep

ObjectiveTo analyze the functional connectivity patterns of the EEG slow-wave activity during the different sleep stages and Cyclic Alternating Pattern (CAP) conditions, using concepts derived from Graph Theory. MethodsWe evaluated spatial patterns of EEG slow-wave synchronization between all possible pairs of electrodes (19) placed over the scalp of 10 sleeping healthy young normal subjects using two graph theoretical measures: the clustering coefficient (Cp) and the characteristic path length (Lp). The measures were obtained during the different sleep stages and CAP conditions from the real EEG connectivity networks and randomized control (surrogate) networks (Cp-s and Lp-s). ResultsCp and Cp/Cp-s increased significantly from wakefulness to sleep while Lp and Lp/Lp-s did not show changes. Cp/Cp-s was higher for A1 phases, compared to B phases of CAP. ConclusionsThe network organization of the EEG slow-wave synchronization during sleep shows features characteristic of small-world networks (high Cp combined with low Lp); this type of organization is slightly but significantly more evident during the CAP A1 subtypes. SignificanceOur results show feasibility of using graph theoretical measures to characterize the complexity of brain networks during sleep and might indicate sleep, and the A1 phases of CAP in particular, as a period during which slow-wave synchronization shows optimal network organization for information processing.

Visual and automatic cyclic alternating pattern (CAP) scoring

The classification of short duration events in the EEG during sleep, as the A stage of the cyclic alternating pattern (CAP) is a tedious and error prone task. The number of events under normal conditions is large (several hundreds), and it is necessary to mark the limits of the events with precision, otherwise the time sensitive classification of the CAP phases (A and B) and specially the scoring of different types of A phases will be compromised. The objective of this study is to verify the feasibility of visual CAP scoring with only one channel of EEG, the evaluation of the inter-scorer agreement in a variety of recordings, and the comparison of the visual scorings with a known automatic scoring system. Sixteen hours of one channel (C4-A1 or C3-A2) of NREM sleep were extracted from eight whole night recordings in European Data Format and presented to the different scorers. The average inter-scorer agreement for all scorers is above 70%, the pair wise inter-scorer agreement found was between 69% up to 77.5%. These values are similar to what has been reported in different type studies. The automatic scoring system has similar performance of the visual scorings. The study also has shown that it is possible to classify the CAP using only one channel of EEG.

The relationship between focal seizures and sleep: An analysis of the cyclic alternating pattern

Purpose The aim of this study was to examine the relationship between focal epileptic seizures and sleep through analysis of the cyclic alternating pattern (CAP). Methods We analyzed the recordings of a total of 56 nocturnal partial seizures (13 occurring as isolated events and 43 “in clusters” during a full-night ambulatory polysomnography) in 12 adult patients affected by localization-related focal epilepsy (7 males, 5 females; mean age 35 + 12.8 years; range 25–71). Results On exact binomial distribution analysis, seizures were more frequent in CAP than in non-CAP sleep, and in CAP phase A than in CAP phase B ( p < 0.001). Seizures occurring in clusters were more frequently associated with CAP sleep ( p < 0.05) than isolated seizures and first seizures of seizure clusters. Increase of CAP rate during the 30-min of sleep period after the occurrence of a seizure was documented in both cluster and isolated seizures. Conclusions Our data indicate that an intra-sleep condition of highly fluctuating vigilance constitutes the real substrate for the occurrence of epileptic seizures regardless of the NREM stage in which they occur. The occurrence of partial seizures during sleep appears to induce sleep instability, which may in turn result in the facilitation of clusters of seizures. Together, these data highlight the potential of sleep fragmentation to modulate intra-sleep seizure occurrence.

Sleep Cyclic Alternating Pattern in Normal Preschool-Aged Children

To evaluate the characteristics of the cyclic alternating pattern (CAP) in the sleep of preschool-aged children in order to obtain normative parameters in this age range. Prospective study. University sleep laboratory. Ten normal healthy subjects (6 girls and 4 boys, mean age 4.6 years; range 3-6 years) underwent polysomnography recordings for 2 consecutive nights in a standard laboratory setting. Sleep data were stored on a computer using a polysomnography digital system (Embla N7000, Medcare, Iceland). Sleep structure was visually scored according to the Rechtschaffen and Kales criteria. The cyclic alternating pattern was visually scored following the criteria by Terzano et al. These criteria were modified for the purposes of this study because it was noticed that, at the age of the group under analysis, most electroencephalogram arousals, often accompanied by electromyogram activation, are expressed at the level of the electroencephalogram by theta frequencies and not alpha or higher frequencies. The CAP rate in preschool-aged children (25.93%) showed a progressive increase with the deepness of sleep, with highest values during non-rapid eye movement (NREM) stage 3 (44.0%) and 4 sleep (46.08%) and lowest values in NREM stage 2 (17.26%). The CAP time showed its longest duration during stage 2 sleep, followed by stage 4, stage 3, and NREM stage 1. The CAP cycle duration showed no differences across NREM stages. The cyclic alternating pattern phase A was longer and phase B was shorter during stage 1 than during stages 2, 3, and 4. A1 phases were the most numerous (63.2%), followed by A2 (21.5%) and by A3 (15.3%). The distribution of A-phase subtypes across NREM sleep stages (A index) showed significant differences for the A1 subtypes that occurred more frequently during stage 3 and 4 sleep than during stages 1 and 2. The A2 index showed no significant differences across NREM sleep stages, while the A3 index was significantly higher during stage 1 sleep than during stages 2, 3, and 4. The analysis of the A1 interval distribution showed a log-normal-like distribution with a peak around 25 seconds for the A1 phases and no clear peak for A2-A3 phases. The analysis of CAP in preschool-aged children is characterized by an increase of CAP rate during slow-wave sleep and a high percentage of A1 phases and A2 phases. However, the lower percentage of A1 paralleled by an increase of A2 could represent a signal of higher sleep instability in this age group as compared with prepubertal school-aged children.

Combined influence of cyclic arousability and EEG synchrony on generalized interictal discharges within the sleep cycle

Purpose: to analyze the activating role of cyclic alternating pattern (CAP) and EEG synchrony on generalized interictal paroxysms in the first part of the night, when all sleep patterns are represented. Methods: nocturnal polysomnographic investigation was accomplished on a randomized series of 18 subjects with an active form of primary generalized epilepsy (PGE), but only six patients showed a complete and regular profile of the first two sleep cycles (SCs). Completeness and regularity of the selected SCs consisted in the absence of intervening wakefulness, in the presence of all sleep stages, and in the identification of three main units, (a) a descending branch, dominated by the build-up of EEG synchrony in the transition from light to deep non-rapid eye movement (NREM) sleep; (b) a trough, where the magnitude of EEG synchrony is greatest and gives rise to stages 3 and 4; (c) an ascending branch characterized by a decrease of EEG synchrony preceding the onset of rapid eye movement (REM) sleep. Generalized paroxysms were evaluated in terms of discharge rates (number of interictal bursts per minute of sleep) and distribution within the investigated sleep parameters. Results: the discharge rates decreased from SC1 to SC2, with higher values quantified during NREM sleep (mean, 2.8) compared with REM sleep (mean, 0.8). Both SCs showed a progressive decrease of activation across the three units, from the highest discharge rates reached during the descending branches (mean, 3.6) to the more attenuated discharge rates during the troughs (mean, 2.4) down to the lowest rates during the ascending limbs (mean, 1.1). The magnitude of activation during the descending branches was closely related to the CAP condition (mean, 5.2) and to the powerful effect of phase A (mean, 13.9). The great majority (82%) of EEG discharges occurring in phase A were distributed within the A1 subtypes (identified by sequences of k-complexes or delta bursts). Conclusions: within the first two SCs, the features of NREM sleep endowed with the major activating power on generalized bursts are represented by the rise of EEG synchrony (descending branch) and by the A phases of CAP involved in the regulation of its build-up.

Automatic detection of cyclic alternating pattern (CAP) sequences in sleep: preliminary results

Objectives: The analysis of cyclic alternating pattern (CAP) provides important microstructural information on arousal instability and on EEG synchrony modulation in the sleep process. This work presents a methodology for automatic classification of the micro-organization of human sleep EEG, using the CAP paradigm.Methods: The classification system is composed of 3 parts: feature extraction, detection and classification. The feature extraction part is an EEG generation model-based maximum likelihood estimator. The detector part for the CAP phases A and B is done by a variable length template matched filter, while the classification criteria part is implemented on a state machine ruled-based decision system.Results and conclusions: The preliminary results of the automatic classifier on a group of 4 middle-aged adults are presented. The high agreement between the detector and visual scoring is very promising in the achievement of a fully automated scoring system, although a more exhaustive evaluation program is needed.

Clinical applications of cyclic alternating pattern

Sleep-related disorders are revisited in the light of the physiological modality of NREM sleep expressed by the cyclic alternating pattern (CAP). Owing to its fluctuating properties on vigilance, muscle tone, and vegetative activities, CAP represents a highly favorable condition for the occurrence of interictal generalized and focal lesional EEG discharges, for motor seizures, and for periodic jerks in nocturnal myoclonus. All these manifestations are significantly associated with the components of activation during CAP, i.e., the A phases. On the contrary, the B phases of CAP appear chronologically linked to inhibitory phenomena in epileptic patients and in nocturnal myoclonus. The two phases of CAP seem especially involved in sleep apnea syndrome, where respiration is interrupted during a phase B and restored during a phase A. CAP rate, that measures the effort of the brain to maintain sleep, is increased by all conditions that induce vigilance instability such as noise, clinical insomnia, interictal EEG paroxysms, nocturnal seizures, periodic leg movements, and in certain extreme pathologic conditions such as Creutzfeldt-Jakob disease and stage 2 coma.